Transforming a Legacy Telecommunications Platform with AWS Cloud Migration
Our client, a leading player in the telecommunications and technology industry, was facing a significant challenge: a large, monolithic legacy application that struggled with scalability, performance bottlenecks, and operational inefficiencies.
Industry
Telecommunications & Tech
Key Technologies
| Category | Tech used |
|---|---|
| Cloud Services | AWS CloudFromation, Amazon EC2, AWS Lammbds |
| Data Engineering | Python, AWS Glue, Terraform, AWS IAM |
| Machine Learning AI | AWS SageMaker, Amazon Bedrock, Google Vertex |
| Infrastructure as Code (IaC) | Terraform, Serverless Framework |
| Deployment & Automation | Jekins, GitHub Actions |
| Project Management | Jira, Confluence, SharePoint |
Summary
A leading telecommunications leader needed to modernize its legacy systems, with a focus on optimizing data handling, enabling AI capabilities, and reducing infrastructure costs. Through an extensive AWS Cloud Migration, a combination of cloud-native tools like AWS CloudFormation, Python, SageMaker, Terraform, and Jenkins, along with new advancements in AI and machine learning, the project successfully streamlined operations and enhanced performance.
Key Services
"Working with Rivka was phenomenal. Their ability to modernize our legacy systems and implement cutting-edge solutions has significantly improved our operational efficiency."
Client Overview
Industry: Telecommunications (Fortune 500)
Company Size: Large enterprise
Region: Global operations
The Challenge
Complex Legacy Migration
Transitioning from a non-code, drag-and-drop legacy system (Asterix) to a fully scalable AWS cloud infrastructure.
Data Security and Governance
Ensuring sensitive data was securely masked and governed during migration and analysis processes.
AI Integration and development
Testing and deploying advanced machine learning models, while maintaining compatibility with existing data workflows.
High Infrastructure Costs
Ongoing expenses related to maintaining the legacy infrastructure.
Deployment Bottlenecks
Lack of automation led to slow and error-prone software releases.
Performance Inefficiencies
The system suffered from latency issues, affecting customer experience.
The Solution
- Seamless AWS Migration:
Developed robust scripts using Python to handle data extraction, transformation, and migration into AWS, ensuring zero data loss.
- Automated Infrastructure Deployment:
Used Terraform and CloudFormation to create reproducible and scalable infrastructure environments.
- Data Governance Framework:
Implemented tools to analyze and mask sensitive data, ensuring compliance with regulatory standards.
Business Impact and Results
The AWS Cloud Migration and AI integration resulted in improved operational efficiency, cost reduction, and enhanced customer service. Key impacts included:
Reduced Operational Costs
By moving away from the expensive legacy Asterix platform, AWS cloud infrastructure reduced costs significantly.
Improved Scalability
The new microservices architecture enabled the telecom company to scale operations seamlessly to handle increased demand.
Faster Data Migration
Automated Python scripts and cloud tools enabled quick and reliable data migration from the legacy system to AWS.
AI-Driven Customer Service
The successful deployment of machine learning models, including chatbots, improved the quality and responsiveness of customer service interactions.
